Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2517-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2517-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
16 Oct 2020
Data description paper |
| 16 Oct 2020
| 16 Oct 2020
Apparent ecosystem carbon turnover time: uncertainties and robust features
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Sujan Koirala
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Markus Reichstein
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Martin Thurner
Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Senckenberganlage 25, 60325 Frankfurt am Main, Germany
Valerio Avitabile
European Commission, Joint Research Centre, Via E. Fermi 2749, 21027 Ispra, Italy
Maurizio Santoro
Gamma Remote Sensing, 3073 Gümligen, Switzerland
Bernhard Ahrens
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Ulrich Weber
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany
Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal
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Atmos. Chem. Phys., 19, 4005–4024, https://doi.org/10.5194/acp-19-4005-2019, https://doi.org/10.5194/acp-19-4005-2019, 2019
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We present a 1-D model to simulate H2O isotopologues of vapor and their vertical fluxes in the first kilometer above the sea surface. The model includes two processes not in earlier Craig–Gordon isotope evaporation models: height-dependent diffusion/mixing and ascending/converging air. Calculated isotopic ratios compare well with data from seven cruises. The model explains how sea surface meteorology can affect atmospheric vapor, precipitation isotope ratios, and paleoisotope records.
Wenli Zhao, Alexander J. Winkler, Markus Reichstein, Rene Orth, and Pierre Gentine
EGUsphere, https://doi.org/10.5194/egusphere-2025-365, https://doi.org/10.5194/egusphere-2025-365, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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We developed a machine learning model that accounts for the memory effects of soil moisture and vegetation to predict Evaporative Fraction (EF) without relying on soil moisture as a direct input. The model accurately predicts EF during dry periods for the unseen sites, highlighting the key of meteorological memory effects. The learned memory effect related to rooting depth and soil water holding capacity could potentially serve as proxies for assessing the plant water stress.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Mélanie Weynants, Chaonan Ji, Nora Linscheid, Ulrich Weber, Miguel D. Mahecha, and Fabian Gans
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-396, https://doi.org/10.5194/essd-2024-396, 2024
Preprint under review for ESSD
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Climate extremes are intensifying. The impacts of heatwaves and droughts can be made worse when they happen at the same time. Dheed is a global database of dry and hot compound extreme events from 1950 to 2022. It can be combined with other data to study the impacts of those events on terrestrial ecosystems, specific species or human societies. Dheed's analysis confirms that extremely dry and hot days have become more common on all continents in recent decades, especially in Europe and Africa.
Laura Dénise Nadolski, Tarek Sebastian El Madany, Jacob Allen Nelson, Arnaud Carrara, Gerardo Moreno, Richard K. F. Nair, Yunpeng Luo, Anke Hildebrandt, Victor Rolo, Markus Reichstein, and Sung-Ching Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-3190, https://doi.org/10.5194/egusphere-2024-3190, 2024
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Semi-arid ecosystems are crucial for Earth's carbon balance and are sensitive to changes in nitrogen (N) and phosphorus (P) levels. Their carbon dynamics are complex and not fully understood. We studied how long-term nutrient changes affect carbon exchange. In summer, N+P changed plant composition and productivity. In transitional seasons, carbon exchange was less weather-dependent with N. Adding N and N+P are increasing carbon exchange variability, driven by grass greenness.
Basil Kraft, Jacob A. Nelson, Sophia Walther, Fabian Gans, Ulrich Weber, Gregory Duveiller, Markus Reichstein, Weijie Zhang, Marc Rußwurm, Devis Tuia, Marco Körner, Zayd Mahmoud Hamdi, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2896, https://doi.org/10.5194/egusphere-2024-2896, 2024
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Global evapotranspiration (ET) can be estimated using machine learning (ML) models optimized on local data and applied to global data. This study explores whether sequential neural networks, which consider past data, perform better than models that do not. The findings show that sequential models struggle with global upscaling, likely due to their sensitivity to data shifts from local to global scales. To improve ML-based upscaling, additional data or integration of physical knowledge is needed.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
EGUsphere, https://doi.org/10.5194/egusphere-2024-2044, https://doi.org/10.5194/egusphere-2024-2044, 2024
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We use an innovative approach to study the Earth's water cycle by blending advanced computer learning techniques with a traditional water cycle model. We developed a model that learns from meteorological data, with a special focus on understanding how vegetation influences water movement. Our model closely aligns with real-world observations, yet there are areas that need improvement. This study opens up new possibilities to better understand the water cycle and its interactions with vegetation.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter Verburg, and Yuki Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2024-2551, https://doi.org/10.5194/egusphere-2024-2551, 2024
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An interdisciplinary collaboration of 35 international researchers from 34 institutions highlighting nine recent findings in biosphere research. Within these themes, they discuss issues arising from climate change and other anthropogenic stressors, and highlight the co-benefits of nature-based solutions and ecosystem services. They discuss recent findings in the context of global trade and international policy frameworks, and highlight lessons for local implementation of nature-based solutions.
Martin Thurner, Kailiang Yu, Stefano Manzoni, Anatoly Prokushkin, Melanie A. Thurner, Zhiqiang Wang, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1794, https://doi.org/10.5194/egusphere-2024-1794, 2024
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Nitrogen concentrations in tree tissues (leaves, branches, stems, and roots) control photosynthesis, growth and respiration, and thus influence vegetation carbon uptake. Our novel database allows us to identify the controls of tree tissue nitrogen concentrations in boreal and temperate forests, such as tree age/size, species and climate. Changes therein will affect tissue N concentrations and thus also vegetation carbon uptake.
Theertha Kariyathan, Ana Bastos, Markus Reichstein, Wouter Peters, and Julia Marshall
EGUsphere, https://doi.org/10.5194/egusphere-2024-1382, https://doi.org/10.5194/egusphere-2024-1382, 2024
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The carbon uptake period (CUP) refers to the time of the year when there is net absorption of CO2 from the atmosphere to the land. Several studies have assessed changes in CUP based on seasonal metrics from CO2 mole fraction measurements to understand the response of terrestrial biosphere to climate variations. However, we find that the CUP derived from CO2 mole fraction measurements are not likely to provide an accurate magnitude of the actual changes occurring over the surface.
Jasper M. C. Denissen, Adriaan J. Teuling, Sujan Koirala, Markus Reichstein, Gianpaolo Balsamo, Martha M. Vogel, Xin Yu, and René Orth
Earth Syst. Dynam., 15, 717–734, https://doi.org/10.5194/esd-15-717-2024, https://doi.org/10.5194/esd-15-717-2024, 2024
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Heat extremes have severe implications for human health and ecosystems. Heat extremes are mostly introduced by large-scale atmospheric circulation but can be modulated by vegetation. Vegetation with access to water uses solar energy to evaporate water into the atmosphere. Under dry conditions, water may not be available, suppressing evaporation and heating the atmosphere. Using climate projections, we show that regionally less water is available for vegetation, intensifying future heat extremes.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
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Porous materials are known to reversibly trap water from the air, even at low humidity. However, this behavior is poorly understood for soils. In this analysis, we test whether eddy covariance is able to measure the so-called adsorption of atmospheric water vapor by soils. We find that this flux occurs frequently during dry nights in a Mediterranean ecosystem, while EC detects downwardly directed vapor fluxes. These results can help to map moisture uptake globally.
Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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We present a methodology to detect inconsistencies in perhaps the most important data source for measurements of ecosystem–atmosphere carbon, water, and energy fluxes. We expect that the derived consistency flags will be relevant for data users and will help in improving our understanding of and our ability to model ecosystem–climate interactions.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
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Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
Atmos. Chem. Phys., 24, 2555–2582, https://doi.org/10.5194/acp-24-2555-2024, https://doi.org/10.5194/acp-24-2555-2024, 2024
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Data-driven eddy-covariance upscaled estimates of the global land–atmosphere net CO2 exchange (NEE) show important mismatches with regional and global estimates based on atmospheric information. To address this, we create a model with a dual constraint based on bottom-up eddy-covariance data and top-down atmospheric inversion data. Our model overcomes shortcomings of each approach, producing improved NEE estimates from local to global scale, helping to reduce uncertainty in the carbon budget.
Marleen Pallandt, Marion Schrumpf, Holger Lange, Markus Reichstein, Lin Yu, and Bernhard Ahrens
EGUsphere, https://doi.org/10.5194/egusphere-2024-186, https://doi.org/10.5194/egusphere-2024-186, 2024
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As soils get warmer due to climate change, SOC decomposes faster because of higher microbial activity, but only with sufficient soil moisture. We modelled how microbes decompose plant litter and microbial residues at different soil depths. We found that deep soil layers are more sensitive than topsoils. SOC is lost from the soil with warming, but this can be mitigated or worsened depending on the type of litter and its sensitivity to temperature. Droughts can reduce warming-induced SOC losses.
Hui Yang, Krzysztof Stereńczak, Zbigniew Karaszewski, and Nuno Carvalhais
EGUsphere, https://doi.org/10.5194/egusphere-2023-2691, https://doi.org/10.5194/egusphere-2023-2691, 2023
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Wood density is crucial for ecological and carbon stock assessment, yet its labor-intensive analysis limits studies across species and spaces. Our study, based on 48,000 samples from Central Europe, reveals that, even without species information, 91% of inter-tree variations can be predicted by vegetation indexes, topography, and soil texture. Importantly, we highlight neglected intra-tree variation, showing substantial variations vertically along the height and radially from the center to bark.
Richard Nair, Yunpeng Luo, Tarek El-Madany, Victor Rolo, Javier Pacheco-Labrador, Silvia Caldararu, Kendalynn A. Morris, Marion Schrumpf, Arnaud Carrara, Gerardo Moreno, Markus Reichstein, and Mirco Migliavacca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2434, https://doi.org/10.5194/egusphere-2023-2434, 2023
Preprint archived
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We studied a Mediterranean ecosystem to understand carbon uptake efficiency and its controls. These ecosystems face potential nitrogen-phosphorus imbalances due to pollution. Analysing six years of carbon data, we assessed controls at different timeframes. This is crucial for predicting such vulnerable regions. Our findings revealed N limitation on C uptake, not N:P imbalance, and strong influence of water availability. whether drought or wetness promoted net C uptake depended on timescale.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
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The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri
Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
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A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
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In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Sinikka Jasmin Paulus, Tarek Sebastian El-Madany, René Orth, Anke Hildebrandt, Thomas Wutzler, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Olaf Kolle, Markus Reichstein, and Mirco Migliavacca
Hydrol. Earth Syst. Sci., 26, 6263–6287, https://doi.org/10.5194/hess-26-6263-2022, https://doi.org/10.5194/hess-26-6263-2022, 2022
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In this study, we analyze small inputs of water to ecosystems such as fog, dew, and adsorption of vapor. To measure them, we use a scaling system and later test our attribution of different water fluxes to weight changes. We found that they occur frequently during 1 year in a dry summer ecosystem. In each season, a different flux seems dominant, but they all mainly occur during the night. Therefore, they could be important for the biosphere because rain is unevenly distributed over the year.
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022, https://doi.org/10.5194/esd-13-1505-2022, 2022
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Quantifying the imprint of large-scale atmospheric circulation dynamics and associated carbon cycle responses is key to improving our understanding of carbon cycle dynamics. Using a statistical model that relies on spatiotemporal sea level pressure as a proxy for large-scale atmospheric circulation, we quantify the fraction of interannual variability in atmospheric CO2 growth rate and the land CO2 sink that are driven by atmospheric circulation variability.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Xin Yu, René Orth, Markus Reichstein, Michael Bahn, Anne Klosterhalfen, Alexander Knohl, Franziska Koebsch, Mirco Migliavacca, Martina Mund, Jacob A. Nelson, Benjamin D. Stocker, Sophia Walther, and Ana Bastos
Biogeosciences, 19, 4315–4329, https://doi.org/10.5194/bg-19-4315-2022, https://doi.org/10.5194/bg-19-4315-2022, 2022
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Identifying drought legacy effects is challenging because they are superimposed on variability driven by climate conditions in the recovery period. We develop a residual-based approach to quantify legacies on gross primary productivity (GPP) from eddy covariance data. The GPP reduction due to legacy effects is comparable to the concurrent effects at two sites in Germany, which reveals the importance of legacy effects. Our novel methodology can be used to quantify drought legacies elsewhere.
Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, https://doi.org/10.5194/bg-19-2805-2022, 2022
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109, https://doi.org/10.5194/hess-26-1089-2022, https://doi.org/10.5194/hess-26-1089-2022, 2022
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, and M. Migliavacca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 49–55, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, 2022
Simon Besnard, Sujan Koirala, Maurizio Santoro, Ulrich Weber, Jacob Nelson, Jonas Gütter, Bruno Herault, Justin Kassi, Anny N'Guessan, Christopher Neigh, Benjamin Poulter, Tao Zhang, and Nuno Carvalhais
Earth Syst. Sci. Data, 13, 4881–4896, https://doi.org/10.5194/essd-13-4881-2021, https://doi.org/10.5194/essd-13-4881-2021, 2021
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Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. In this paper, we introduced a new global distribution of forest age inferred from forest inventory, remote sensing and climate data in support of a better understanding of the global dynamics in the forest water and carbon cycles.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Yeonuk Kim, Monica Garcia, Laura Morillas, Ulrich Weber, T. Andrew Black, and Mark S. Johnson
Hydrol. Earth Syst. Sci., 25, 5175–5191, https://doi.org/10.5194/hess-25-5175-2021, https://doi.org/10.5194/hess-25-5175-2021, 2021
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Here, we present a novel physically based evaporation model to demonstrate that vertical relative humidity (RH) gradients from the land surface to the atmosphere tend to evolve towards zero due to land–atmosphere equilibration processes. Collapsing RH gradients on daily to yearly timescales indicate an emergent land–atmosphere equilibrium, making it possible to determine evapotranspiration using only meteorological information, independent of land surface conditions and vegetation controls.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
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Roots play a key role in our Earth system. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (~ 1 km) root biomass dataset. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
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Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
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Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021, https://doi.org/10.5194/bg-18-39-2021, 2021
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Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO2 of different vegetation types at the global scale. We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny. This implies different water management strategies of forests but also a lack of sensitivity to remote-sensing-derived vegetation activity.
B. Kraft, M. Jung, M. Körner, and M. Reichstein
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1537–1544, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, 2020
Daniel E. Pabon-Moreno, Talie Musavi, Mirco Migliavacca, Markus Reichstein, Christine Römermann, and Miguel D. Mahecha
Biogeosciences, 17, 3991–4006, https://doi.org/10.5194/bg-17-3991-2020, https://doi.org/10.5194/bg-17-3991-2020, 2020
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Ecosystem CO2 uptake changes in time depending on climate conditions. In this study, we analyze how different climate variables affect the timing when CO2 uptake is at a maximum (DOYGPPmax). We found that the joint effects of radiation, temperature, and vapor pressure deficit are the most relevant controlling factors of DOYGPPmax and that if they increase, DOYGPPmax will happen earlier. These results help us to better understand how CO2 uptake could be affected by climate change.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
René Orth, Georgia Destouni, Martin Jung, and Markus Reichstein
Biogeosciences, 17, 2647–2656, https://doi.org/10.5194/bg-17-2647-2020, https://doi.org/10.5194/bg-17-2647-2020, 2020
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Drought duration is a key control of the large-scale biospheric drought response.
Thereby, the vegetation responds linearly to drought duration at large spatial scales.
The slope of the linear relationship between the vegetation drought response and drought duration is steeper in drier climates.
Guido Kraemer, Gustau Camps-Valls, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 17, 2397–2424, https://doi.org/10.5194/bg-17-2397-2020, https://doi.org/10.5194/bg-17-2397-2020, 2020
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To closely monitor the state of our planet, we require systems that can monitor
the observation of many different properties at the same time. We create
indicators that resemble the behavior of many different simultaneous
observations. We apply the method to create indicators representing the
Earth's biosphere. The indicators show a productivity gradient and a water
gradient. The resulting indicators can detect a large number of changes and
extremes in the Earth system.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Lin Yu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, https://doi.org/10.5194/gmd-13-783-2020, 2020
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In this paper, we have developed a new soil organic carbon model that describes the formation and turnover of soil organic matter in a more mechanistic manner. With this model, we are able to better represent how microorganisms and nutrient processes influence the below-ground carbon storage and better explain some observed features of soil organic matter. We hope this model can increase our confidence in predictions of future climate change, particularly on how soil can mitigate the process.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Javier Pacheco-Labrador, Tarek S. El-Madany, M. Pilar Martin, Rosario Gonzalez-Cascon, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Tiana Hammer, Heiko Moossen, Kathrin Henkel, Olaf Kolle, David Martini, Vicente Burchard, Christiaan van der Tol, Karl Segl, Markus Reichstein, and Mirco Migliavacca
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-501, https://doi.org/10.5194/bg-2019-501, 2020
Revised manuscript not accepted
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The new generation of sensors on-board satellites have the potential to provide richer information about the function of vegetation than before. This information, nowadays missing, is fundamental to improve our understanding and prediction of carbon and water cycles, and therefore to anticipate effects and responses to Climate Change. In this manuscript we propose a method to exploit the data provided by these satellites to successfully obtain this information key to face Climate Change.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Sven Boese, Martin Jung, Nuno Carvalhais, Adriaan J. Teuling, and Markus Reichstein
Biogeosciences, 16, 2557–2572, https://doi.org/10.5194/bg-16-2557-2019, https://doi.org/10.5194/bg-16-2557-2019, 2019
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This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration. We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation. Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
Richard K. F. Nair, Kendalynn A. Morris, Martin Hertel, Yunpeng Luo, Gerardo Moreno, Markus Reichstein, Marion Schrumpf, and Mirco Migliavacca
Biogeosciences, 16, 1883–1901, https://doi.org/10.5194/bg-16-1883-2019, https://doi.org/10.5194/bg-16-1883-2019, 2019
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We investigated how nutrient availability affects seasonal timing of root growth and death in a Spanish savanna, adapted to a long summer drought. We found that nitrogen (N) additions led to more root biomass but number of roots was higher with N and phosphorus together. These effects were strongly affected by the time of year. In autumn root growth occurred after leaf production. This has implications for how we understand biomass production and carbon uptake in these systems.
Xiahong Feng, Eric S. Posmentier, Leslie J. Sonder, and Naixin Fan
Atmos. Chem. Phys., 19, 4005–4024, https://doi.org/10.5194/acp-19-4005-2019, https://doi.org/10.5194/acp-19-4005-2019, 2019
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We present a 1-D model to simulate H2O isotopologues of vapor and their vertical fluxes in the first kilometer above the sea surface. The model includes two processes not in earlier Craig–Gordon isotope evaporation models: height-dependent diffusion/mixing and ascending/converging air. Calculated isotopic ratios compare well with data from seven cruises. The model explains how sea surface meteorology can affect atmospheric vapor, precipitation isotope ratios, and paleoisotope records.
Xiaolu Tang, Nuno Carvalhais, Catarina Moura, Bernhard Ahrens, Sujan Koirala, Shaohui Fan, Fengying Guan, Wenjie Zhang, Sicong Gao, Vincenzo Magliulo, Pauline Buysse, Shibin Liu, Guo Chen, Wunian Yang, Zhen Yu, Jingjing Liang, Leilei Shi, Shenyan Pu, and Markus Reichstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-37, https://doi.org/10.5194/bg-2019-37, 2019
Preprint withdrawn
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Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass. This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls. Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.
Milan Flach, Sebastian Sippel, Fabian Gans, Ana Bastos, Alexander Brenning, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 15, 6067–6085, https://doi.org/10.5194/bg-15-6067-2018, https://doi.org/10.5194/bg-15-6067-2018, 2018
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Northern forests enhanced their productivity during and before the 2010 Russian mega heatwave. We scrutinize this issue with a novel type of multivariate extreme event detection approach. Forests compensate for 54 % of the carbon losses in agricultural ecosystems due to vulnerable conditions in spring and better water management in summer. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.
Stefano Manzoni, Petr Čapek, Philipp Porada, Martin Thurner, Mattias Winterdahl, Christian Beer, Volker Brüchert, Jan Frouz, Anke M. Herrmann, Björn D. Lindahl, Steve W. Lyon, Hana Šantrůčková, Giulia Vico, and Danielle Way
Biogeosciences, 15, 5929–5949, https://doi.org/10.5194/bg-15-5929-2018, https://doi.org/10.5194/bg-15-5929-2018, 2018
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Carbon fixed by plants and phytoplankton through photosynthesis is ultimately stored in soils and sediments or released to the atmosphere during decomposition of dead biomass. Carbon-use efficiency is a useful metric to quantify the fate of carbon – higher efficiency means higher storage and lower release to the atmosphere. Here we summarize many definitions of carbon-use efficiency and study how this metric changes from organisms to ecosystems and from terrestrial to aquatic environments.
Thomas Wutzler, Antje Lucas-Moffat, Mirco Migliavacca, Jürgen Knauer, Kerstin Sickel, Ladislav Šigut, Olaf Menzer, and Markus Reichstein
Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, https://doi.org/10.5194/bg-15-5015-2018, 2018
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Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere–atmosphere interactions. However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data. Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning. The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082, https://doi.org/10.5194/hess-22-4061-2018, https://doi.org/10.5194/hess-22-4061-2018, 2018
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In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Paul Bodesheim, Martin Jung, Fabian Gans, Miguel D. Mahecha, and Markus Reichstein
Earth Syst. Sci. Data, 10, 1327–1365, https://doi.org/10.5194/essd-10-1327-2018, https://doi.org/10.5194/essd-10-1327-2018, 2018
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We provide continuous half-hourly carbon and energy fluxes for 2001 to 2014 at 0.5° spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). In addition, we provide a derived product that only contains monthly average diurnal cycles but which also enables us to study the important characteristics of subdaily patterns at a global scale.
Jacob A. Nelson, Nuno Carvalhais, Mirco Migliavacca, Markus Reichstein, and Martin Jung
Biogeosciences, 15, 2433–2447, https://doi.org/10.5194/bg-15-2433-2018, https://doi.org/10.5194/bg-15-2433-2018, 2018
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Plants have typical daily carbon uptake and water loss cycles. However, these cycles may change under periods of duress, such as water limitation. Here we identify two types of patterns in response to water limitations: a tendency to lose more water in the morning than afternoon and a decoupling of the carbon and water cycles. The findings show differences in responses by trees and grasses and suggest that morning shifts may be more efficient at gaining carbon per unit water used.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
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Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Iulia Ilie, Peter Dittrich, Nuno Carvalhais, Martin Jung, Andreas Heinemeyer, Mirco Migliavacca, James I. L. Morison, Sebastian Sippel, Jens-Arne Subke, Matthew Wilkinson, and Miguel D. Mahecha
Geosci. Model Dev., 10, 3519–3545, https://doi.org/10.5194/gmd-10-3519-2017, https://doi.org/10.5194/gmd-10-3519-2017, 2017
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Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO2 fluxes to climate often remain uncertain. The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach. When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
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Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Milan Flach, Fabian Gans, Alexander Brenning, Joachim Denzler, Markus Reichstein, Erik Rodner, Sebastian Bathiany, Paul Bodesheim, Yanira Guanche, Sebastian Sippel, and Miguel D. Mahecha
Earth Syst. Dynam., 8, 677–696, https://doi.org/10.5194/esd-8-677-2017, https://doi.org/10.5194/esd-8-677-2017, 2017
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Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate. We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing. We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches. The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.
Sven Boese, Martin Jung, Nuno Carvalhais, and Markus Reichstein
Biogeosciences, 14, 3015–3026, https://doi.org/10.5194/bg-14-3015-2017, https://doi.org/10.5194/bg-14-3015-2017, 2017
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For plants, the ratio of carbon uptake to water loss by transpiration is usually thought to depend on characteristic properties (their adaption to water scarcity) and the dryness of the atmosphere at any given moment. We show that, on the ecosystem scale, radiation has an independent effect on this ratio that had not been previously considered. When including this variable in models, predictions of transpiration improve considerably.
Sebastian Sippel, Jakob Zscheischler, Miguel D. Mahecha, Rene Orth, Markus Reichstein, Martha Vogel, and Sonia I. Seneviratne
Earth Syst. Dynam., 8, 387–403, https://doi.org/10.5194/esd-8-387-2017, https://doi.org/10.5194/esd-8-387-2017, 2017
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The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
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We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale
Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, https://doi.org/10.5194/bg-13-4291-2016, 2016
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We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
O. Perez-Priego, J. Guan, M. Rossini, F. Fava, T. Wutzler, G. Moreno, N. Carvalhais, A. Carrara, O. Kolle, T. Julitta, M. Schrumpf, M. Reichstein, and M. Migliavacca
Biogeosciences, 12, 6351–6367, https://doi.org/10.5194/bg-12-6351-2015, https://doi.org/10.5194/bg-12-6351-2015, 2015
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Sun-induced chlorophyll fluorescence and photochemical reflectance index revealed controls of climate and nutrient availability on photosynthesis (gross primary production, GPP). Meteo-driven models (MMs) were unable to describe nutrient-induced effects on GPP. Important implications can be derived from these results, and uncertainties in the prediction of global GPP still remain when MMs do not account for plant nutrient availability.
S. Hashimoto, N. Carvalhais, A. Ito, M. Migliavacca, K. Nishina, and M. Reichstein
Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, https://doi.org/10.5194/bg-12-4121-2015, 2015
A. C. Spessa, R. D. Field, F. Pappenberger, A. Langner, S. Englhart, U. Weber, T. Stockdale, F. Siegert, J. W. Kaiser, and J. Moore
Nat. Hazards Earth Syst. Sci., 15, 429–442, https://doi.org/10.5194/nhess-15-429-2015, https://doi.org/10.5194/nhess-15-429-2015, 2015
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
X. Wu, F. Babst, P. Ciais, D. Frank, M. Reichstein, M. Wattenbach, C. Zang, and M. D. Mahecha
Biogeosciences, 11, 3057–3068, https://doi.org/10.5194/bg-11-3057-2014, https://doi.org/10.5194/bg-11-3057-2014, 2014
S. Vicca, M. Bahn, M. Estiarte, E. E. van Loon, R. Vargas, G. Alberti, P. Ambus, M. A. Arain, C. Beier, L. P. Bentley, W. Borken, N. Buchmann, S. L. Collins, G. de Dato, J. S. Dukes, C. Escolar, P. Fay, G. Guidolotti, P. J. Hanson, A. Kahmen, G. Kröel-Dulay, T. Ladreiter-Knauss, K. S. Larsen, E. Lellei-Kovacs, E. Lebrija-Trejos, F. T. Maestre, S. Marhan, M. Marshall, P. Meir, Y. Miao, J. Muhr, P. A. Niklaus, R. Ogaya, J. Peñuelas, C. Poll, L. E. Rustad, K. Savage, A. Schindlbacher, I. K. Schmidt, A. R. Smith, E. D. Sotta, V. Suseela, A. Tietema, N. van Gestel, O. van Straaten, S. Wan, U. Weber, and I. A. Janssens
Biogeosciences, 11, 2991–3013, https://doi.org/10.5194/bg-11-2991-2014, https://doi.org/10.5194/bg-11-2991-2014, 2014
J. Zscheischler, M. Reichstein, S. Harmeling, A. Rammig, E. Tomelleri, and M. D. Mahecha
Biogeosciences, 11, 2909–2924, https://doi.org/10.5194/bg-11-2909-2014, https://doi.org/10.5194/bg-11-2909-2014, 2014
B. Ahrens, M. Reichstein, W. Borken, J. Muhr, S. E. Trumbore, and T. Wutzler
Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, https://doi.org/10.5194/bg-11-2147-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
B. Badawy, C. Rödenbeck, M. Reichstein, N. Carvalhais, and M. Heimann
Biogeosciences, 10, 6485–6508, https://doi.org/10.5194/bg-10-6485-2013, https://doi.org/10.5194/bg-10-6485-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
M. C. Braakhekke, T. Wutzler, C. Beer, J. Kattge, M. Schrumpf, B. Ahrens, I. Schöning, M. R. Hoosbeek, B. Kruijt, P. Kabat, and M. Reichstein
Biogeosciences, 10, 399–420, https://doi.org/10.5194/bg-10-399-2013, https://doi.org/10.5194/bg-10-399-2013, 2013
G. Lasslop, M. Migliavacca, G. Bohrer, M. Reichstein, M. Bahn, A. Ibrom, C. Jacobs, P. Kolari, D. Papale, T. Vesala, G. Wohlfahrt, and A. Cescatti
Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, https://doi.org/10.5194/bg-9-5243-2012, 2012
Related subject area
Biogeosciences and biodiversity
High-resolution carbon cycling data from 2019 to 2021 measured at six Austrian long-term ecosystem research sites
An organic matter database (OMD): consolidating global residue data from agriculture, fisheries, forestry and related industries
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
A post-processed carbon flux dataset for 34 eddy covariance flux sites across the Heihe River Basin, China
A spectral–structural characterization of European temperate, hemiboreal, and boreal forests
VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring
Crop-specific management history of phosphorus fertilizer input (CMH-P) in the croplands of the United States: reconciliation of top-down and bottom-up data sources
Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI
A synthesized field survey database of vegetation and active-layer properties for the Alaskan tundra (1972–2020)
Mapping global leaf inclination angle (LIA) based on field measurement data
Century Long Reconstruction of Gridded Phosphorus Surplus Across Europe (1850–2019)
TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation
Global nitrous oxide budget (1980–2020)
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Spatial mapping of key plant functional traits in terrestrial ecosystems across China
LegacyVegetation 1.0: Global reconstruction of vegetation composition and forest cover from pollen archives of the last 50 ka
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
Reference maps of soil phosphorus for the pan-Amazon region
Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020
Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022
Investigating limnological processes and modern sedimentation at Lake Żabińskie, northeast Poland: a decade-long multi-variable dataset, 2012–2021
Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020
Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada
Quantifying exchangeable base cations in permafrost: a reserve of nutrients about to thaw
Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
The Portuguese Large Wildfire Spread database (PT-FireSprd)
Thirty-meter map of young forest age in China
GRiMeDB: the Global River Methane Database of concentrations and fluxes
A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests
Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT
A global database on holdover time of lightning-ignited wildfires
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
A new habitat map of the Lena Delta in Arctic Siberia based on field and remote sensing datasets
Mammals in the Chornobyl Exclusion Zone's Red Forest: a motion-activated camera trap study
Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years
AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America
TiP-Leaf: a dataset of leaf traits across vegetation types on the Tibetan Plateau
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
Global climate-related predictors at kilometer resolution for the past and future
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020
Global land surface 250 m 8 d fraction of absorbed photosynthetically active radiation (FAPAR) product from 2000 to 2021
Rates and timing of chlorophyll-a increases and related environmental variables in global temperate and cold-temperate lakes
Harmonized gap-filled datasets from 20 urban flux tower sites
Holocene spatiotemporal millet agricultural patterns in northern China: a dataset of archaeobotanical macroremains
The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil
Airborne SnowSAR data at X and Ku bands over boreal forest, alpine and tundra snow cover
Thomas Dirnböck, Michael Bahn, Eugenio Diaz-Pines, Ika Djukic, Michael Englisch, Karl Gartner, Günther Gollobich, Johannes Ingrisch, Barbara Kitzler, Karl Knaebel, Johannes Kobler, Andreas Maier, Armin Malli, Ivo Offenthaler, Johannes Peterseil, Gisela Pröll, Sarah Venier, Christoph Wohner, Sophie Zechmeister-Boltenstern, Anita Zolles, and Stephan Glatzel
Earth Syst. Sci. Data, 17, 685–702, https://doi.org/10.5194/essd-17-685-2025, https://doi.org/10.5194/essd-17-685-2025, 2025
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Long-term observation sites have been established in six Austrian locations, covering major ecosystem types such as forests, grasslands, and wetlands. The purpose of these observations is to measure baselines for assessing the impacts of extreme climate events on the carbon cycle. The collected datasets include meteorological variables, soil temperature and moisture, carbon dioxide fluxes, and tree stem growth in forests at a resolution of 15–60 min between 2019 and 2021.
Gudeta Weldesemayat Sileshi, Edmundo Barrios, Johannes Lehmann, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 17, 369–391, https://doi.org/10.5194/essd-17-369-2025, https://doi.org/10.5194/essd-17-369-2025, 2025
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Agricultural, fishery, forestry and agro-processing activities produce large quantities of residues, by-products and waste materials every year. Here, we present a global organic matter database (OMD), the first of its kind, consolidating estimates of residues and by-products potentially available for use in a circular bio-economy. It also provides definitions, typologies and methods to aid consistent classification, estimation and reporting of the various residues and by-products.
Kelly S. Aho, Kaelin M. Cawley, Robert T. Hensley, Robert O. Hall Jr., Walter K. Dodds, and Keli J. Goodman
Earth Syst. Sci. Data, 16, 5563–5578, https://doi.org/10.5194/essd-16-5563-2024, https://doi.org/10.5194/essd-16-5563-2024, 2024
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Gas exchange is fundamental to many biogeochemical processes in streams and depends on the degree of gas saturation and the gas transfer velocity (k). Currently, k is harder to measure than concentration. Here, we present a processing pipeline to estimate k from tracer-gas experiments conducted in 22 streams by the National Ecological Observatory Network. The processed dataset (n = 339) represents the largest compilation of standardized k estimates available.
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-370, https://doi.org/10.5194/essd-2024-370, 2024
Revised manuscript accepted for ESSD
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In this study, carbon flux and auxiliary meteorological data were post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River Basin. Eighteen sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1,513 site-months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová
Earth Syst. Sci. Data, 16, 5069–5087, https://doi.org/10.5194/essd-16-5069-2024, https://doi.org/10.5194/essd-16-5069-2024, 2024
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Radiative transfer models play a key role in monitoring vegetation using remote sensing data such as satellite or airborne images. The development of these models has been hindered by a lack of comprehensive ground reference data on structural and spectral characteristics of forests. Here, we reported datasets on the structural and spectral properties of temperate, hemiboreal, and boreal European forest stands. We anticipate that these data will have wide use in remote sensing applications.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
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VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Peiyu Cao, Bo Yi, Franco Bilotto, Carlos Gonzalez Fischer, Mario Herrero, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 4557–4572, https://doi.org/10.5194/essd-16-4557-2024, https://doi.org/10.5194/essd-16-4557-2024, 2024
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This article presents a spatially explicit time series dataset reconstructing crop-specific phosphorus fertilizer application rates, timing, and methods at a 4 km × 4 km resolution in the United States from 1850 to 2022. We comprehensively characterized the spatio-temporal dynamics of P fertilizer management over the last 170 years by considering cross-crop variations. This dataset will greatly contribute to the field of agricultural sustainability assessment and Earth system modeling.
Chad A. Burton, Sami W. Rifai, Luigi J. Renzullo, and Albert I. J. M. Van Dijk
Earth Syst. Sci. Data, 16, 4389–4416, https://doi.org/10.5194/essd-16-4389-2024, https://doi.org/10.5194/essd-16-4389-2024, 2024
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Understanding vegetation response to environmental change requires accurate, long-term data on vegetation condition (VC). We evaluated existing satellite VC datasets over Australia and found them lacking, so we developed a new VC dataset for Australia, AusENDVI. It can be used for studying Australia's changing vegetation dynamics and downstream impacts on the carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
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The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Sijia Li and Hongliang Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-325, https://doi.org/10.5194/essd-2024-325, 2024
Revised manuscript accepted for ESSD
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Leaf inclination angle (LIA) is a vital parameter in radiative transfer, rainfall interception, evapotranspiration, photosynthesis, and hydrological processes. However, global LIA knowledge is still lacking. This study generated the first global 500 m LIA products by gap-filling LIA measurement data. The global LIA is 41.47°±9.55° and increases with latitude. The LIA products would enhance our understanding of global LIA and assist remote sensing retrieval and land surface modeling studies.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-294, https://doi.org/10.5194/essd-2024-294, 2024
Revised manuscript accepted for ESSD
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Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in EU-27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu
Earth Syst. Sci. Data, 16, 2789–2809, https://doi.org/10.5194/essd-16-2789-2024, https://doi.org/10.5194/essd-16-2789-2024, 2024
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To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Daju Wang, Peiyang Ren, Xiaosheng Xia, Lei Fan, Zhangcai Qin, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 16, 2465–2481, https://doi.org/10.5194/essd-16-2465-2024, https://doi.org/10.5194/essd-16-2465-2024, 2024
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This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-486, https://doi.org/10.5194/essd-2023-486, 2024
Revised manuscript accepted for ESSD
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This study reconstructed past vegetation and forest cover from a global data set of pollen counts from sediment and peat cores. A model was applied to correct for differences in pollen production between different plants and modern remote-sensing forest cover was used to adjust the necessary correction factors and improve the reconstruction even further. Accurate data on past vegetation is invaluable for the investigation of vegetation-climate dynamics and the validation of vegetation models.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
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Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
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Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
João Paulo Darela-Filho, Anja Rammig, Katrin Fleischer, Tatiana Reichert, Laynara Figueiredo Lugli, Carlos Alberto Quesada, Luis Carlos Colocho Hurtarte, Mateus Dantas de Paula, and David M. Lapola
Earth Syst. Sci. Data, 16, 715–729, https://doi.org/10.5194/essd-16-715-2024, https://doi.org/10.5194/essd-16-715-2024, 2024
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Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it interacts with carbon cycle in ecosystems. To apply these models, it is important to know the distribution of phosphorus in soil. In this study we estimated the distribution of phosphorus in the Amazon region. The results showed a clear gradient of soil development and P content. These maps can help improve ecosystem models and generate new hypotheses about phosphorus availability in the Amazon.
Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge
Earth Syst. Sci. Data, 16, 277–293, https://doi.org/10.5194/essd-16-277-2024, https://doi.org/10.5194/essd-16-277-2024, 2024
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This study utilized 24,552 in situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020. These phenology maps are the first gridded, independent and reliable phenology data sources for China, offering a high spatial resolution of 0.1° and an average deviation of about 10 days. It contributes to more comprehensive research on plant phenology and climate change.
Jiabin Pu, Kai Yan, Samapriya Roy, Zaichun Zhu, Miina Rautiainen, Yuri Knyazikhin, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 15–34, https://doi.org/10.5194/essd-16-15-2024, https://doi.org/10.5194/essd-16-15-2024, 2024
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Long-term global LAI/FPAR products provide the fundamental dataset for accessing vegetation dynamics and studying climate change. This study develops a sensor-independent LAI/FPAR climate data record based on the integration of Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products and applies advanced gap-filling techniques. The SI LAI/FPAR CDR provides a valuable resource for researchers studying vegetation dynamics and their relationship to climate change in the 21st century.
Wojciech Tylmann, Alicja Bonk, Dariusz Borowiak, Paulina Głowacka, Kamil Nowiński, Joanna Piłczyńska, Agnieszka Szczerba, and Maurycy Żarczyński
Earth Syst. Sci. Data, 15, 5093–5103, https://doi.org/10.5194/essd-15-5093-2023, https://doi.org/10.5194/essd-15-5093-2023, 2023
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We present a dataset from the decade-long monitoring of Lake Żabińskie, a hardwater and eutrophic lake in northeast Poland. The lake contains varved sediments, which form a unique archive of past environmental variability. The monitoring program was designed to capture a pattern of relationships between meteorological conditions, limnological processes, and modern sedimentation and to verify if meteorological and limnological phenomena can be precisely tracked with varves.
Sen Cao, Muyi Li, Zaichun Zhu, Zhe Wang, Junjun Zha, Weiqing Zhao, Zeyu Duanmu, Jiana Chen, Yaoyao Zheng, Yue Chen, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, https://doi.org/10.5194/essd-15-4877-2023, 2023
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The long-term global leaf area index (LAI) products are critical for characterizing vegetation dynamics under environmental changes. This study presents an updated GIMMS LAI product (GIMMS LAI4g; 1982−2020) based on PKU GIMMS NDVI and massive Landsat LAI samples. With higher accuracy than other LAI products, GIMMS LAI4g removes the effects of orbital drift and sensor degradation in AVHRR data. It has better temporal consistency before and after 2000 and a more reasonable global vegetation trend.
Muyi Li, Sen Cao, Zaichun Zhu, Zhe Wang, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, https://doi.org/10.5194/essd-15-4181-2023, 2023
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Long-term global Normalized Difference Vegetation Index (NDVI) products support the understanding of changes in vegetation under environmental changes. This study generates a consistent global NDVI product (PKU GIMMS NDVI) from 1982–2022 that eliminates the issue of orbital drift and sensor degradation in Advanced Very High Resolution Radiometer (AVHRR) data. More accurate than its predecessor (GIMMS NDVI3g), it shows high temporal consistency with MODIS NDVI in describing vegetation trends.
Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, and Natalia De Leon Gatti
Earth Syst. Sci. Data, 15, 3963–3990, https://doi.org/10.5194/essd-15-3963-2023, https://doi.org/10.5194/essd-15-3963-2023, 2023
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A genomic, phenomic, and climate database for maize phenotype predictability in the US and Canada is introduced. The database encompasses climate from multiple sources and OMICS from the Genomes to Fields initiative (G2F) data from 2014 to 2021, including codes for input data quality and consistency controls. Earth system modelers and breeders can use CLIM4OMICS since it interconnects the climate and biological system sciences. CLIM4OMICS is designed to foster phenotype predictability.
Elisabeth Mauclet, Maëlle Villani, Arthur Monhonval, Catherine Hirst, Edward A. G. Schuur, and Sophie Opfergelt
Earth Syst. Sci. Data, 15, 3891–3904, https://doi.org/10.5194/essd-15-3891-2023, https://doi.org/10.5194/essd-15-3891-2023, 2023
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Permafrost ecosystems are limited in nutrients for vegetation development and constrain the biological activity to the active layer. Upon Arctic warming, permafrost degradation exposes organic and mineral soil material that may directly influence the capacity of the soil to retain key nutrients for vegetation growth and development. Here, we demonstrate that the average total exchangeable nutrient density (Ca, K, Mg, and Na) is more than 2 times higher in the permafrost than in the active layer.
Anna G. Boegehold, Ashley M. Burtner, Andrew C. Camilleri, Glenn Carter, Paul DenUyl, David Fanslow, Deanna Fyffe Semenyuk, Casey M. Godwin, Duane Gossiaux, Thomas H. Johengen, Holly Kelchner, Christine Kitchens, Lacey A. Mason, Kelly McCabe, Danna Palladino, Dack Stuart, Henry Vanderploeg, and Reagan Errera
Earth Syst. Sci. Data, 15, 3853–3868, https://doi.org/10.5194/essd-15-3853-2023, https://doi.org/10.5194/essd-15-3853-2023, 2023
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Western Lake Erie suffers from cyanobacterial harmful algal blooms (HABs) despite decades of international management efforts. In response, the US National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs. Here we describe the data collected from this monitoring program from 2012 to 2021.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
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We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
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Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros
Earth Syst. Sci. Data, 15, 2879–2926, https://doi.org/10.5194/essd-15-2879-2023, https://doi.org/10.5194/essd-15-2879-2023, 2023
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The Global River Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters and concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
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We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
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We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Beatriz P. Cazorla, Javier Cabello, Andrés Reyes, Emilio Guirado, Julio Peñas, Antonio J. Pérez-Luque, and Domingo Alcaraz-Segura
Earth Syst. Sci. Data, 15, 1871–1887, https://doi.org/10.5194/essd-15-1871-2023, https://doi.org/10.5194/essd-15-1871-2023, 2023
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This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada (Spain), a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTSER) network.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
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We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-36, https://doi.org/10.5194/essd-2023-36, 2023
Revised manuscript accepted for ESSD
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The Lena Delta is the largest river delta in the Arctic, and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
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Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Yili Jin, Haoyan Wang, Jie Xia, Jian Ni, Kai Li, Ying Hou, Jing Hu, Linfeng Wei, Kai Wu, Haojun Xia, and Borui Zhou
Earth Syst. Sci. Data, 15, 25–39, https://doi.org/10.5194/essd-15-25-2023, https://doi.org/10.5194/essd-15-25-2023, 2023
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The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits from 468 species of 1692 individuals, covering a great proportion of species and vegetation types on the highest plateau in the world. This work is the first plant trait dataset that represents all of the alpine vegetation on the TP, which is not only an update of the Chinese plant trait database, but also a great contribution to the global trait database.
Timon Miesner, Ulrike Herzschuh, Luidmila A. Pestryakova, Mareike Wieczorek, Evgenii S. Zakharov, Alexei I. Kolmogorov, Paraskovya V. Davydova, and Stefan Kruse
Earth Syst. Sci. Data, 14, 5695–5716, https://doi.org/10.5194/essd-14-5695-2022, https://doi.org/10.5194/essd-14-5695-2022, 2022
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We present data which were collected on expeditions to the northeast of the Russian Federation. One table describes the 226 locations we visited during those expeditions, and the other describes 40 289 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements or use data (as presented here).
Philipp Brun, Niklaus E. Zimmermann, Chantal Hari, Loïc Pellissier, and Dirk Nikolaus Karger
Earth Syst. Sci. Data, 14, 5573–5603, https://doi.org/10.5194/essd-14-5573-2022, https://doi.org/10.5194/essd-14-5573-2022, 2022
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Using mechanistic downscaling, we developed CHELSA-BIOCLIM+, a set of 15 biologically relevant, climate-related variables at unprecedented resolution, as a basis for environmental analyses. It includes monthly time series for 38+ years and 30-year averages for three future periods and three emission scenarios. Estimates matched well with station measurements, but few biases existed. The data allow for detailed assessments of climate-change impact on ecosystems and their services to societies.
Shaoyang He, Yongqiang Zhang, Ning Ma, Jing Tian, Dongdong Kong, and Changming Liu
Earth Syst. Sci. Data, 14, 5463–5488, https://doi.org/10.5194/essd-14-5463-2022, https://doi.org/10.5194/essd-14-5463-2022, 2022
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This study developed a daily, 500 m evapotranspiration and gross primary production product (PML-V2(China)) using a locally calibrated water–carbon coupled model, PML-V2, which was well calibrated against observations at 26 flux sites across nine land cover types. PML-V2 (China) performs satisfactorily in the plot- and basin-scale evaluations compared with other mainstream products. It improved intra-annual ET and GPP dynamics, particularly in the cropland ecosystem.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
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The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
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Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
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We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Keyang He, Houyuan Lu, Jianping Zhang, and Can Wang
Earth Syst. Sci. Data, 14, 4777–4791, https://doi.org/10.5194/essd-14-4777-2022, https://doi.org/10.5194/essd-14-4777-2022, 2022
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Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic and Bronze ages in northern China. Temporally, millet agriculture underwent a dramatic transition from low-yield broomcorn to high-yield foxtail millet around 6000 cal. a BP under the influence of climate and population. Spatially, millet agriculture spread westward and northward from the mid-lower Yellow River (MLY) to the agro-pastoral ecotone (APE) around 6000 cal. a BP and diversified afterwards.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
Short summary
Short summary
We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
Short summary
Short summary
The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
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Short summary
The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback. In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback.
The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback....
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